Tower Top Daily Average

library(tidyverse)
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top <- read.csv('Tower_Top_0066_5306_0586_Full.csv')
top$Temperature <- ((top$Temp - 32)*5)/9
top <- separate(top, Time, into = c('hours','minutes'))
top$hours <- as.numeric(top$hours)
top <- na.omit(top)

for (i in 1:nrow(top)) { 
  if (top$minutes[i] == 30) {
    top$hours[i] <- top$hours[i] + 0.5
  }
}

top2 <- top %>% group_by(Date, hours) 
top2$Place <- "Top2"

boxplot(Temperature ~ hours, data = top2, col = "salmon", main = "Boxplots of Tower Top Temperatures", xlab = "Hours from Midnight", ylab = "Temperature in Celcius")

Tower Middle Daily Average

middle <- read.csv('Tower_Middle_7433.csv')
middle <- separate(middle, Time, into = c('hours','minutes'))
middle$hours <- as.numeric(middle$hours)
middle$Temperature <- ((middle$Temp - 32)*5)/9

for (i in 1:nrow(middle)) { 
  if (middle$minutes[i] == 30) {
    middle$hours[i] <- middle$hours[i] + 0.5
  }
}

middle2 <- middle %>% group_by(Date, hours)
middle2$Place <- "Middle2"

boxplot(Temperature ~ hours, data = middle2, col = "green", main = "Boxplots of Tower Middle Temperatures", xlab = "Hours from Midnight", ylab = "Temperature in Celcius")

Tower Top + Tower Middle Comparison

library(plotly)
## 
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
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mis <- middle %>% arrange(Date, hours) 
mis$Place <- "Middle"
for (i in 1:nrow(mis)) { 
  if (mis$minutes[i] == 45) {
    mis$hours[i] <- mis$hours[i] + 0.5
  }
}
mis2 <- mis %>% distinct(Date, hours, .keep_all = T) %>% group_by(hours) %>% mutate(Average = mean(Temp, na.rm = T)) %>% slice(1)
mis3 <- top  %>% arrange(Date, hours) 
mis3$Place <- "Top"
for (i in 1:nrow(mis3)) { 
  if (mis3$minutes[i] == 45) {
    mis3$hours[i] <- mis3$hours[i] + 0.5
  }
}

mis4 <- mis3 %>% distinct(Date, hours, .keep_all = T) %>% group_by(hours) %>% mutate(Average = mean(Temp, na.rm = T)) %>% slice(1)
mis4$Place <- "Top"

topmiddle <- rbind(mis2, mis4)

topmiddle$hours <- as.numeric(topmiddle$hours)

plot1 <- ggplot(topmiddle, aes(hours, Average, color = Place)) + geom_smooth(aes(x = hours, y = Average), method = "lm",
              formula = y ~ poly(x, 23), se = FALSE) + geom_errorbar(alpha = 0.3, aes(ymin = Average - sd(Average, na.rm = T), ymax = Average + sd(Average, na.rm = T), width = 0.2)) 

plot1

Tower Base Daily Average

base <- read.csv('Tower Base 4377.csv')
base$Temperature <- ((base$Temp - 32)*5)/9
base <- separate(base, Time, into = c('hours','minutes'))
base$hours <- as.numeric(base$hours)
base <- na.omit(base)

for (i in 1:nrow(base)) { 
  if (base$minutes[i] == 30) {
    base$hours[i] <- base$hours[i] + 0.5
  }
}

base2 <- base %>% group_by(Date, hours)
base2$Place <- "Base2"

boxplot(Temperature ~ hours, data = base2, col = "salmon", main= "Boxplots of Tower Base Temperatures", xlab = "Hours from Midnight", ylab = "Temperature in Celcius")

Plots of Tower

mis <- middle %>% arrange(Date, hours) 
mis$Place <- "Middle"
mis$minutes <- as.numeric(mis$minutes)
mis$hours <- as.numeric(mis$hours)

for (i in 1:nrow(mis)) { 
  if (mis$minutes[i] == 45) {
    mis$hours[i] <- mis$hours[i] + 0.5
  }
}
mis2 <- mis %>% distinct(Date, hours, .keep_all = T) %>% group_by(hours) %>% mutate(Average = mean(Temp, na.rm = T)) %>% slice(1)

mis3 <- top  %>% arrange(Date, hours) 
mis3$Place <- "Top"

mis3$minutes <- as.numeric(mis3$minutes)
mis3$hours <- as.numeric(mis3$hours)
for (i in 1:nrow(mis3)) { 
  if (mis3$minutes[i] == 45) {
    mis3$hours[i] <- mis3$hours[i] + 0.5
  }
}

mis4 <- mis3 %>% distinct(Date, hours, .keep_all = T) %>% group_by(hours) %>% mutate(Average = mean(Temp, na.rm = T)) %>% slice(1)
mis4$Place <- "Top"

mis5 <- base  %>% arrange(Date, hours) 
mis5$Place <- "Base"
mis5$minutes <- as.numeric(mis5$minutes)
mis5$hours <- as.numeric(mis5$hours)
for (i in 1:nrow(mis5)) { 
  if (mis5$minutes[i] == 45) {
    mis5$hours[i] <- mis5$hours[i] + 0.5
  }
}

mis6 <- mis5 %>% distinct(Date, hours, .keep_all = T) %>% group_by(hours) %>% mutate(Average = mean(Temp, na.rm = T)) %>% slice(1)
mis6$Place <- "Base"

topmiddle <- rbind(mis2, mis6, mis4)

topmiddle$hours <- as.numeric(topmiddle$hours)

ggplot(topmiddle, aes(hours, Average, color = Place)) + geom_smooth(aes(x = hours, y = Average), method = "lm", formula = y ~ poly(x, 23), se = FALSE) + geom_errorbar(alpha = 0.2, aes(ymin = Average - sd(Average, na.rm = T), ymax = Average + sd(Average, na.rm = T), width = 0.2)) + geom_rect(aes(xmin = 5.75, xmax = 6.25, ymin = 20, ymax = 30),
               fill = "transparent", color = "black", size = 0.5, linetype = 2) + ggtitle("Plots of Tower")

ggplotly(plot1)
library(tidyverse)
MP150 <- read.csv("MP150_5354_7432.csv")
Lago0066 <- read.csv("Lago 0066.csv")
Lago5353 <- read.csv("Lago 5353.csv")

MP150 Plot Daily Average

MP150 <- read.csv("MP150_5354_7432.csv")
MP150 <- separate(MP150, Date...Time, into = c("dates", "Time"), sep = " ")
MP150$dates <- as.Date(MP150$dates, "%m/%d/%Y")
MP150 <- separate(MP150, Time, into = c('hours','minutes'))
MP150$hours <- as.numeric(MP150$hours)

for (i in 1:nrow(MP150)) { 
  if (MP150$minutes[i] == 30) {
    MP150$hours[i] <- MP150$hours[i] + 0.5
  }
}

MP1502 <- MP150 %>% group_by(dates, hours)

boxplot(Temperature ~ hours, data = MP1502, col = "salmon", main= "Boxplots of MP150 Temperatures", xlab = "Hours from Midnight", ylab = "Temperature in Celcius")

Lago Plot Daily Average

Lago0066 <- read.csv("Lago 0066.csv")
Lago5353 <- read.csv("Lago 5353.csv")
Lago5353 <- Lago5353[,-1]
colnames(Lago5353) <- c("Number", "Date...Time", "Temperature", "Humidity")
colnames(Lago0066) <- c("Number", "Date...Time", "Temperature", "Humidity")
Lago <- rbind(Lago0066, Lago5353)
Lago$Temperature <- ((Lago$Temperature - 32)*5)/9
Lago <- separate(Lago, Date...Time, into = c("dates", "Time"), sep = " ")
Lago$dates <- as.Date(Lago$dates, "%m/%d/%Y")
Lago <- separate(Lago, Time, into = c('hours','minutes'))

Lago$hours <- as.numeric(Lago$hours)

for (i in 1:nrow(Lago)) { 
  if (Lago$minutes[i] == 30) {
    Lago$hours[i] <- Lago$hours[i] + 0.5
  }
}

Lago2 <- Lago %>% group_by(dates, hours)

boxplot(Temperature ~ hours, data = Lago2, col = "salmon", main= "Boxplots of Lago Temperatures", xlab = "Hours from Midnight", ylab = "Temperature in Celcius")

hello <- Lago2 %>% filter(dates == "2019-08-04")

Parahuaco Plot Daily Average

Parahuaco <- read.csv("Parahuaco RH.csv")
Parahuaco <- separate(Parahuaco, Date...Time, into = c("dates", "Time"), sep = " ")
Parahuaco$dates <- as.Date(Parahuaco$dates, "%m/%d/%Y")
Parahuaco <- separate(Parahuaco, Time, into = c('hours','minutes'))
Parahuaco$hours <- as.numeric(Parahuaco$hours)

for (i in 1:nrow(Parahuaco)) { 
  if (Parahuaco$minutes[i] == 30) {
    Parahuaco$hours[i] <- Parahuaco$hours[i] + 0.5
  }
}

boxplot(Temperature ~ hours, data = Parahuaco, col = "salmon", main= "Boxplots of Parahuaco Temperatures", xlab = "Hours from Midnight", ylab = "Temperature in Celcius")

GP Plot Daily Average

GP <- read.csv("GP RH.csv")
GP <- GP[,-1]
GP <- separate(GP, Date...Time, into = c("dates", "Time"), sep = " ")
GP$dates <- as.Date(GP$dates, "%m/%d/%Y")
GP <- separate(GP, Time, into = c('hours','minutes'))
GP$hours <- as.numeric(GP$hours)

for (i in 1:nrow(GP)) { 
  if (GP$minutes[i] == 30) {
    GP$hours[i] <- GP$hours[i] + 0.5
  }
}

GP2 <- GP %>% group_by(dates, hours)

boxplot(Temperature ~ hours, data = GP, col = "salmon", main= "Boxplots of GP Temperatures", xlab = "Hours from Midnight (2019-07-26)", ylab = "Temperature in Celcius")

Murcialago (Rest) Daily Average

Murcialago <- read.csv("Murcialago5306.csv")
Murcialago <- separate(Murcialago, Date...Time, into = c("dates", "Time"), sep = " ")
Murcialago$dates <- as.Date(Murcialago$dates, "%m/%d/%Y")
Murcialago <- separate(Murcialago, Time, into = c('hours','minutes'))
Murcialago$hours <- as.numeric(Murcialago$hours)

for (i in 1:nrow(Murcialago)) { 
  if (Murcialago$minutes[i] == 30) {
    Murcialago$hours[i] <- Murcialago$hours[i] + 0.5
  }
}

Murcialago2 <- Murcialago %>% group_by(dates, hours)

boxplot(Temperature ~ hours, data = Murcialago2, col = "salmon", main= "Boxplots of Murcialago Temperatures", xlab = "Hours from Midnight", ylab = "Temperature in Celcius")

Parahuaco (Rest) Daily Average

Parahuaco <- read.csv("Parahuaco RH.csv")
Parahuaco <- separate(Parahuaco, Date...Time, into = c("dates", "Time"), sep = " ")
Parahuaco$dates <- as.Date(Parahuaco$dates, "%m/%d/%Y")
Parahuaco <- separate(Parahuaco, Time, into = c('hours','minutes'))
Parahuaco$hours <- as.numeric(Parahuaco$hours)

for (i in 1:nrow(Parahuaco)) { 
  if (Parahuaco$minutes[i] == 30) {
    Parahuaco$hours[i] <- Parahuaco$hours[i] + 0.5
  }
}

Parahuaco2 <- Parahuaco %>% group_by(dates, hours)

boxplot(Temperature ~ hours, data = Parahuaco2, col = "salmon", main= "Boxplots of Parahuaco Temperatures", xlab = "Hours from Midnight", ylab = "Temperature in Celcius")

Danta (Rest) Daily Average

dataset <- read.csv("Denta Region RH.csv")
dataset <- dataset[,-1]

colnames(dataset) <- c("Number", "Date...Time", "Temperature", "Humidity")

Danta <- separate(dataset, Date...Time, into = c("dates", "Time"), sep = " ")
Danta$dates <- as.Date(Danta$dates, "%m/%d/%Y")
Danta <- separate(Danta, Time, into = c('hours','minutes'))
Danta$hours <- as.numeric(Danta$hours)

for (i in 1:nrow(Danta)) { 
  if (Danta$minutes[i] == 30) {
    Danta$hours[i] <- Danta$hours[i] + 0.5
  }
}

Danta2 <- Danta %>% group_by(dates, hours)

boxplot(Temperature ~ hours, data = Danta2, col = "salmon", main= "Boxplots of Danta Temperatures", xlab = "Hours from Midnight", ylab = "Temperature in Celcius")

Titi Cabin (Sleep) Daily Average

Cabin <- read.csv("TitiCabin9223.csv")
Cabin <- separate(Cabin, Date...Time, into = c("dates", "Time"), sep = " ")
Cabin$dates <- as.Date(Cabin$dates, "%m/%d/%Y")
Cabin <- separate(Cabin, Time, into = c('hours','minutes'))
Cabin$hours <- as.numeric(Cabin$hours)

for (i in 1:nrow(Cabin)) { 
  if (Cabin$minutes[i] == 30) {
    Cabin$hours[i] <- Cabin$hours[i] + 0.5
  }
}

Cabin2 <- Cabin %>% group_by(dates, hours)

boxplot(Temperature ~ hours, data = Cabin2, col = "salmon", main= "Boxplots of Titi Cabin Temperatures", xlab = "Hours from Midnight", ylab = "Temperature in Celcius")

Titi Trail (Sleep) Daily Average

Trail <- read.csv("TitiTrail2115.csv")
Trail <- separate(Trail, Date...Time, into = c("dates", "Time"), sep = " ")
Trail$dates <- as.Date(Trail$dates, "%m/%d/%Y")
Trail <- separate(Trail, Time, into = c('hours','minutes'))
Trail$hours <- as.numeric(Trail$hours)

for (i in 1:nrow(Trail)) { 
  if (Trail$minutes[i] == 30) {
    Trail$hours[i] <- Trail$hours[i] + 0.5
  }
}

Trail2 <- Trail %>% group_by(dates, hours)

boxplot(Temperature ~ hours, data = Trail2, col = "salmon", main= "Boxplots of Titi Trail Temperatures", xlab = "Hours from Midnight", ylab = "Temperature in Celcius")

## Comparison of Tower top middle bottom Temperatures

top <- read.csv('Tower_Top_0066_5306_0586_Full.csv')
top$Temp <- ((top$Temp - 32)*5)/9
top <- separate(top, Time, into = c('hours','minutes'))
top$hours <- as.numeric(top$hours)
top <- na.omit(top)
middle <- read.csv('Tower_Middle_7433.csv')
middle <- separate(middle, Time, into = c('hours','minutes'))
middle$hours <- as.numeric(middle$hours)
middle$Temp <- ((middle$Temp - 32)*5)/9
for (i in 1:nrow(top)) { 
  if (top$minutes[i] == 30| top$minutes[i]==45) {
    top$hours[i] <- top$hours[i] + 0.5
  }
}
for (i in 1:nrow(middle)) { 
  if (middle$minutes[i] == 30| middle$minutes[i]==45) {
    middle$hours[i] <- middle$hours[i] + 0.5
  }
}
base <- read.csv('Tower Base 4377.csv')
base$Temp <- ((base$Temp - 32)*5)/9
base <- separate(base, Time, into = c('hours','minutes'))
base$hours <- as.numeric(base$hours)
base <- na.omit(base)
for (i in 1:nrow(base)) { 
  if (base$minutes[i] == 30 | base$minutes[i]==45) {
    base$hours[i] <- base$hours[i] + 0.5
  }
}
base2 <- base %>% group_by(hours) %>% summarize(Temperature = mean(Temp, na.rm = T))
base2$Location <- "Base"
top2 <- top %>% group_by(hours) %>% summarize(Temperature = mean(Temp, na.rm = T))
middle2 <- middle %>% group_by(hours) %>% summarize(Temperature = mean(Temp, na.rm = T))
top2$Location <- "Top"
middle2$Location <- "Middle"
tmb <- rbind(top2, middle2, base2)

ggplot(tmb, aes(hours, Temperature)) +
  geom_point(aes(color = Location)) + geom_line(aes(color = Location)) + labs(title = "Comparison of Tower Top Middle Bottom Temperature")

Plot of all Sites

library(plotly)
Cabin22 <- Cabin2  %>% group_by(hours) %>% summarise(Temperature = mean(Temperature, na.rm = T)) %>% mutate(Location = "Titi Cabin")
Danta22 <- Danta2 %>% group_by(hours) %>% summarise(Temperature = mean(Temperature, na.rm = T)) %>% mutate(Location = "Danta")
MP15022 <- MP1502 %>% group_by(hours) %>% summarise(Temperature = mean(Temperature, na.rm = T)) %>% mutate(Location = "MP150")
Trail22 <- Trail2 %>% group_by(hours) %>% summarise(Temperature = mean(Temperature, na.rm = T)) %>% mutate(Location = "Titi Cabin")
Parahuaco22 <- Parahuaco2 %>% group_by(hours) %>% summarise(Temperature = mean(Temperature, na.rm = T)) %>% mutate(Location = "Parahuaco")
Murcialago22 <- Murcialago2 %>% group_by(hours) %>% summarise(Temperature = mean(Temperature, na.rm = T)) %>% mutate(Location = "Murcialago")
GP22 <- GP2 %>% group_by(hours) %>% summarise(Temperature = mean(Temperature, na.rm = T)) %>% mutate(Location = "GP")
AllSites <- rbind(top2, middle2, base2, Cabin22, Danta22, MP15022, Trail22, Parahuaco22, Murcialago22, GP22)
allplots <- ggplot(AllSites, aes(hours, Temperature, color = Location)) + geom_smooth(se = F, size = 0.35)
ggplotly(allplots)
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'